Diagnosis device and diagnosis method

Abstract

To improve accuracy of instrument preventive maintenance.SOLUTION: A diagnosis device 100 according to the present invention includes: an acquisition unit 11 that acquires acceleration data and velocity data indicating vibrations of a bearing from an IoT sensor 1, a measuring instrument 2, and a tablet terminal 3; and a diagnosis unit 12 that diagnoses abnormalities in the bearing on the basis of the acquired acceleration data and velocity data. The diagnosis device 100 further includes a display control unit that displays an acceleration diagnosis result obtained from the acceleration data in accordance with a shaft diameter of the bearing, a velocity diagnosis result obtained from the velocity data in accordance with motor output of a motor that rotationally drives the bearing and a comprehensive diagnosis result based on the acceleration data and velocity data.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a diagnostic device and a diagnostic method. [Background technology]

[0002] In recent years, technological developments related to preventive maintenance of facility equipment for buildings, etc. have been progressing, and related inventions have been made public. For example, Patent Document 1 discloses a bearing device that diagnoses bearing abnormalities by comparing the outputs of two strain gauges attached to the retaining members of two bearings. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2023-81149 A Summary of the Invention [Problem to be solved by the invention]

[0004] The invention of Patent Document 1 uses only strain gauges for bearing abnormality diagnosis, so the amount of information obtained from the diagnosis results is limited. From this perspective, an object of the present invention is to improve the accuracy of preventive maintenance of equipment. [Means for solving the problem]

[0005] The present invention provides a diagnostic device for solving the above-mentioned problems, comprising: an acquisition unit that acquires acceleration data and velocity data indicative of vibration of a bearing; and a diagnosing unit that diagnoses an abnormality in the bearing based on the acquired acceleration data and speed data. The diagnostic method of the present invention also includes the steps of obtaining acceleration and velocity data indicative of vibrations in a bearing; and diagnosing an abnormality in the bearing based on the acquired acceleration data and velocity data. According to the present invention, it is possible to diagnose abnormalities such as lack of oil or scratches in rolling bearings from acceleration data, and abnormalities such as bearing imbalance or misalignment from speed data. In this way, a lot of information can be obtained from the diagnosis results. Furthermore, with the recent spread of IoT (Internet of Things) devices, the number of targets for bearing abnormality diagnosis has expanded to a large number. In response to these circumstances, the present invention enables bearing abnormality diagnosis to be performed easily and over a wide area at an early stage, thereby improving the work efficiency of preventive equipment maintenance.

[0006] Here, it is preferable to further provide a display control unit that displays an acceleration diagnosis result obtained from the acceleration data and corresponding to the shaft diameter of the bearing, a speed diagnosis result obtained from the speed data and corresponding to the motor output of a motor that rotates the bearing, and a comprehensive diagnosis result covering the acceleration data and the speed data. This allows the diagnosis results to be visualized, making it easy to identify abnormalities.

[0007] It is also preferable that the diagnosing unit diagnoses an abnormality in the bearing based on at least one of an installation environment of a device including the bearing and the number of years the device has been installed. This makes it possible to improve the accuracy of diagnosing bearing abnormalities. Effect of the Invention

[0008] According to the present invention, it is possible to improve the efficiency of preventive maintenance work for equipment. [Brief description of the drawings]

[0009] [Figure 1] FIG. 2 is a functional configuration diagram of the diagnostic device according to the present embodiment. [Diagram 2] FIG. 13 is an explanatory diagram of an example of an acceleration determination table. [Diagram 3] FIG. 11 is an explanatory diagram of an example of a speed determination table. [Figure 4] FIG. 13 is an explanatory diagram of an example of a comprehensive judgment table. [Diagram 5]13 is a display example of a diagnosis result. [Figure 6] 13A and 13B are explanatory diagrams of other examples of the comprehensive judgment table. [Figure 7] 2 is a flowchart of the diagnostic method of the present embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, the embodiment of the present invention will be described in detail with reference to the drawings. Each drawing is merely a schematic illustration to allow a sufficient understanding of the present invention. Therefore, the present invention is not limited to the illustrated examples. In each drawing, common or similar components are denoted by the same reference numerals, and duplicated explanations thereof will be omitted.

[0011] [composition] 1 is a functional configuration diagram of a diagnostic device according to the present embodiment. The diagnostic device 100 is an information processing device that diagnoses abnormalities in a bearing provided in a target device. The target device is, for example, a pump or an air conditioner installed in a building, but is not limited to these.

[0012] The diagnostic device 100 includes hardware such as an input unit, an output unit, a control unit, and a storage unit. For example, when the control unit is configured with a CPU (Central Processing Unit), information processing by a computer including the control unit is realized by program execution processing by the CPU. Also, a storage unit included in the computer stores various programs for realizing the functions of the computer by instructions from the CPU. This realizes collaboration between software and hardware. The programs can be provided by recording them on a recording medium or via a network. The diagnostic device 100 may be communicably connected to a console (not shown) used by a user. The connection may be wired or wireless. The console can display the processing results of the diagnostic device 100 and input requests to the diagnostic device 100.

[0013] Furthermore, the diagnostic device 100 is communicably connected to an IoT sensor 1 (IoT is an abbreviation for Internet of Things), a measuring device 2, and a tablet terminal 3. The connection may be wired or wireless. The IoT sensor 1 is a sensor attached to a target device. The IoT sensor 1 can constantly detect vibrations of a bearing included in the target device. The IoT sensor 1 is, for example, but not limited to, an acceleration sensor that can detect the acceleration of a bearing or a speed sensor that can detect the speed of a bearing. The acceleration sensor may be, for example, but not limited to, a capacitance type or a piezoelectric type. The speed sensor may be, for example, but not limited to, an eddy current type, a Hall effect type, or a variable reluctance type. The measuring device 2 is a vibration meter logger that measures the vibration of a bearing included in the target device. The measuring device 2 is equipped with, for example, a probe with a magnetic base, and the user can measure the acceleration and speed of the bearing by applying the probe to a predetermined position of the target device. The tablet terminal 3 is an information terminal that can input data related to the target device. A user can input data related to vibration of a bearing included in the target device by operating the tablet terminal 3. The input data may be acceleration data or speed data indicating vibration, text data such as a memo, or image data obtained by photographing the target device, but is not limited to these.

[0014] The diagnostic device 100 includes an acquisition unit 11, a diagnosis unit 12, and a display control unit 13. The diagnostic device 100 also stores a basic information DB 21, a measurement information DB 22, an acceleration determination table 31, a speed determination table 32, and a comprehensive determination table 33. "DB" is an abbreviation for database.

[0015] The acquisition unit 11 acquires data from the IoT sensor 1, the measuring device 2, and the tablet terminal 3. The acquired data is, for example, acceleration data and speed data indicating vibration of a bearing of the target device, but is not limited to these. The acceleration data and speed data may be, for example, waveform data collected at a predetermined sampling timing over a predetermined frequency band. In addition, the data may be an effective value of acceleration (RMS: Root Mean Square) and an effective value of speed obtained by analyzing the waveform data. The diagnosing unit 12 diagnoses the bearing of the target device for abnormality based on the acquired acceleration data and speed data. The diagnosing unit 12 can use at least one of the acceleration determination table 31, the speed determination table 32, and the overall determination table 33 when making the diagnosis. The display control unit 13 displays the diagnosis result by the diagnosis unit 12. The display destination may be, for example, the display unit of the diagnosis device 100, or the display unit of a console communicably connected to the diagnosis device 100. The diagnosis result may be displayed on a screen or may be displayed by print output. The diagnosis result may be, for example, an acceleration diagnosis result using the acceleration judgment table 31, a speed diagnosis result using the speed judgment table 32, and a comprehensive diagnosis result using the comprehensive judgment table 33, but is not limited to these.

[0016] The basic information DB21 is a DB that stores basic information related to the target equipment. The basic information includes, for example, but is not limited to, a "customer name" indicating the customer who uses the target equipment, a "building name" indicating the building in which the target equipment is installed, an "equipment No." that is an identifier of the target equipment, an "equipment name" indicating the type of the target equipment, a "manufacturer" indicating the manufacturer of the target equipment, a "model number" of the target equipment, a "bearing model number" of the bearing of the target equipment, a "shaft diameter" [mm] of the bearing, a "motor output" [kW] of the motor that drives the bearing, a "number of poles" [P] of the motor, and an "installation date" [yyyy / mm / dd] indicating the installation time of the target equipment. The measurement information DB 22 is a DB that stores measurement information related to the target device. The measurement information includes, for example, a "measurement date" indicating the measurement time, a measurement position indicating the measurement location of the target device (e.g., the mounting position of the IoT sensor 1, the position where the probe of the measuring device 2 is placed), a "vibration measuring device" indicating the type of the measuring device 2 used for the measurement, an "acceleration RMS" [m / s 2 ], "speed RMS" [mm / s] which is a measured value of speed, "operating frequency" [Hz] which indicates the frequency in the operating state of the target equipment, "rotational speed" [RPM] which indicates the rotational speed of the bearings of the target equipment (or the rotational speed of the motor driving the bearings), "current" [A] which indicates the current value in the operating state of the target equipment, "temperature" [°C] which indicates the temperature in the operating state of the target equipment, and "displacement" [mm] which indicates the displacement in the operating state of the target equipment. The acceleration data and speed data acquired by the acquisition unit 11 may be the measurement information, or a value obtained by performing a predetermined analysis process or calculation process on the acceleration data and speed data may be the measurement information.

[0017] The acceleration determination table 31 is a table showing the relationship between the effective value of acceleration (acceleration RMS) obtained by measuring the bearing (at the measurement position) and the abnormality of the bearing. FIG. 2 is an explanatory diagram of an example of the acceleration determination table. The abnormality of the bearing can be divided into four stages, "danger", "warning", "passable", and "good", in descending order of the degree of abnormality. Basically, the larger the effective value of acceleration, the higher the degree of abnormality. In addition, when the effective value of acceleration is the same, the smaller the shaft diameter of the bearing, the higher the degree of abnormality. The acceleration determination table 31 divides the range of shaft diameters into four (25 mm or less, 50 mm or less, 75 mm or less, and 100 mm or less), and shows the range of abnormality for each of the four shaft diameter ranges. The diagnosis unit 12 can determine which abnormality level, "danger", "warning", "passable", or "good", the target bearing of the target device corresponds to by applying the shaft diameter read from the basic information DB 21 and the effective value of acceleration read from the measurement information DB 22 to the acceleration determination table 31. Note that multiple types of acceleration determination tables 31 can be prepared for each rotation speed of the target bearing of the target device (or for each number of poles of the motor). The acceleration determination table 31 in Fig. 2 is a table for a rotation speed of 1500 rpm.

[0018] The speed judgment table 32 is a table showing the relationship between the effective value of the speed (speed RMS) obtained by measuring the bearing (at the measurement position) and the abnormality of the bearing. FIG. 3 is an explanatory diagram of an example of the speed judgment table. Bearing abnormalities can be divided into four stages, "danger," "warning," "fair," and "good," in descending order of the degree of abnormality. Basically, the higher the effective value of the speed, the higher the degree of abnormality. In addition, when the effective value of the speed is the same, the lower the motor output, the higher the degree of abnormality. The speed judgment table 32 divides the range of motor output into four (less than 15 kW, 15 kW to 75 kW, 75 kW or more with a hard foundation (meaning that the installation strength of the target equipment is high), and 75 kW or more with a soft foundation (meaning that the installation strength of the target equipment is low)), and shows the range of abnormality for each of the four ranges of motor output. The diagnosis unit 12 can determine whether the target bearing of the target equipment is at a level of abnormality of “Danger”, “Warning”, “Fair” or “Good” by applying the motor output read from the basic information DB 21 and the effective speed value read from the measurement information DB 22 to the speed determination table 32.

[0019] The overall judgment table 33 is a table showing the relationship between the effective acceleration value, the effective speed value, and the bearing abnormality obtained by measuring the bearing (at the measurement position). Fig. 4 is an explanatory diagram of an example of the overall judgment table. The diagnosis unit 12 uses a predetermined conversion formula to determine an acceleration judgment value from the effective value of the acceleration. The acceleration judgment value takes one of three values: 3.0, 6.0, or 9.0. In the overall judgment table 33, bearing abnormalities regarding acceleration can be classified into three levels, "danger," "warning," and "passable," in descending order of degree of abnormality. When the acceleration judgment value is 3.0, the degree of abnormality of the bearing focusing on acceleration is judged to be "passable." When the acceleration judgment value is 6.0, the degree of abnormality of the bearing focusing on acceleration is judged to be "warning." When the acceleration judgment value is 9.0, the degree of abnormality of the bearing focusing on acceleration is judged to be "danger." The diagnosis unit 12 uses a predetermined conversion formula to determine a speed judgment value from the effective speed value. The speed judgment value takes one of three values: 2.0, 6.0, and 12.0. In the overall judgment table 33, bearing abnormalities can be classified into three levels for speed: "Danger," "Warning," and "Passible," in descending order of degree of abnormality. When the speed judgment value is 2.0, the degree of abnormality of the bearing focusing on the speed is judged to be "Passable." When the speed judgment value is 6.0, the degree of abnormality of the bearing focusing on the speed is judged to be "Warning." When the speed judgment value is 12.0, the degree of abnormality of the bearing focusing on the speed is judged to be "Danger."

[0020] The diagnosis unit 12 calculates a total judgment value as follows: Total judgment value=(Acceleration judgment value) 1 / 2 × (speed judgment value) 1 / 2 That is, the overall judgment value can take one of the seven values ​​of 2.4, 3.5, 4.2, 6.0, 7.3, 8.5, and 10.4. In the overall judgment table 33, bearing abnormalities can be classified into three levels, "Danger," "Caution," and "Passible," in descending order of abnormality level. When the overall judgment value is 2.4 or 3.5, the bearing abnormality level is judged as "Passable." When the overall judgment value is 4.2 or 6.0, the bearing abnormality level is judged as "Warning." When the overall judgment value is 7.3, 8.5, or 10.4, the bearing abnormality level is judged as "Danger." The overall judgment table 33 can be said to be a judgment table that places weight on the speed judgment, assuming that bearing failure occurs due to a mechanical abnormality. The diagnosis unit 12 applies to the overall judgment table 33 an acceleration judgment value calculated from the effective value of acceleration and a speed judgment value calculated from the effective value of speed, thereby determining whether the target bearing of the target equipment is at a level of abnormality of “Danger”, “Caution”, or “Acceptable”.

[0021] The display control unit 13 displays on the display destination the diagnosis results indicating the degree of abnormality of the bearings using the acceleration judgment table 31, the speed judgment table 32, and the overall judgment table 33. Fig. 5 is an example of a display of the diagnosis results. The diagnosis result 50 is divided into a first area 51, a second area 52, a third area 53, and a fourth area 54, but other areas may be provided.

[0022] In the first area 51, basic information about the target device stored in the basic information DB 21 is displayed. The second area 52 displays the measurement information stored in the measurement information DB 22 for the target device. The second area 52 can display all the measurement information for each measurement. For example, as shown in Fig. 5, the measurement information for the current measurement (August 24, 2022) and the measurement information for the previous measurement (July 24, 2022) can be displayed. Even if two or more measurements are taken on the same day, the measurement information for each measurement can be displayed all at once.

[0023] In the third area 53, an acceleration diagnosis result 53a using the acceleration judgment table 31 and a speed diagnosis result 53b using the speed judgment table 32 are displayed for the target device. The acceleration diagnosis result 53a and the speed diagnosis result 53b can be displayed together for each measurement. For example, as shown in Fig. 5, the current (●) and previous (◆) of the acceleration diagnosis result 53a and the speed diagnosis result 53b are plotted at the corresponding positions. In the fourth area 54, the overall diagnosis result for the target device is displayed using the overall judgment table 33. The overall diagnosis result can be displayed collectively for each measurement. For example, as shown in Fig. 5, the current overall diagnosis result (frame 54a) and the previous overall diagnosis result (frame 54b) are displayed.

[0024] The display control unit 13 can display, as the diagnosis result, for example, suggestions for future diagnostic policies (e.g., whether a detailed diagnosis is necessary, and the frequency of measurement (once a month)), image data that can assist in the diagnosis (e.g., a photo of the exterior of the target device, and a photo taken of the measurement position when measuring with measuring device 2), and text data indicating findings entered by the user who referred to the diagnosis result.

[0025] For example, from the acceleration diagnosis result 53a obtained from the acceleration data, it is possible to diagnose abnormalities such as lack of oil or scratches on the rolling bearing. Also, from the speed diagnosis result 53b obtained from the speed data, it is possible to diagnose abnormalities such as imbalance or misalignment of the bearing. Also, from the overall diagnosis result, it is possible to determine the necessity of a detailed diagnosis. According to FIG. 5, the current acceleration diagnosis result 53a (●) indicates the abnormality level of "warning", suggesting the necessity of a detailed diagnosis (e.g., bearing diagnosis by FFT (Fast Fourier Transform) analysis, CF (Crest Factor) judgment). However, since the current overall diagnosis result (frame 54a) indicates the abnormality level of "passable", it is possible to determine that a detailed diagnosis is not yet necessary. In this way, it is possible to reduce the burden of bearing diagnosis. Also, even if the current overall diagnosis result (frame 54a) indicates the abnormality level of "passable", it is possible to semi-quantitatively confirm that the abnormality level is progressing when compared with the previous overall diagnosis result (frame 54b). Therefore, by tracking the history of diagnostic results, it is possible to roughly estimate the timing when the status will change from "OK" to "Warning," i.e., to some extent to predict when a detailed diagnosis will be required. In this way, the comprehensive diagnostic results can be a useful tool for preventive maintenance of equipment.

[0026] The contents of the overall judgment table 33 can be changed as appropriate. Fig. 6 is an explanatory diagram (a) and (b) of other examples of the overall judgment table. For example, when the installation environment of the target equipment is poor and it is expected that foreign matter will be mixed into the bearings or the bearing lubricant will deteriorate, it is preferable to use the overall judgment table 33-1 shown in Fig. 6(a). Compared to the overall judgment table 33, the overall judgment table 33-1 can be said to be a judgment table that places more weight on acceleration judgment (stricter diagnosis of acceleration). The diagnosis unit 12 can diagnose abnormalities in the bearings using the overall judgment table 33-1.

[0027] Also, for example, when the target equipment is old and both acceleration and speed are expected to show large values, it is preferable to use the overall judgment table 33-2 shown in Fig. 6(b).Compared to the overall judgment table 33, the overall judgment table 33-1 is a judgment table in which the weight of the speed judgment is lowered, and the acceleration judgment and the speed judgment are weighted to the same degree (the strictness of the diagnosis for acceleration and the strictness of the diagnosis for speed are made to the same degree).The diagnosis unit 12 can diagnose abnormalities in the bearings by using the overall judgment table 33-2.

[0028] [process] A diagnostic method showing the processing of the diagnostic device 100 will be described. FIG. 7 is a flowchart of the diagnostic method of this embodiment. First, the acquisition unit 11 of the diagnostic device 100 acquires acceleration data and speed data indicating the vibration of the bearing of the target device from at least one of the IoT sensor 1, the measuring device 2, and the tablet terminal 3 (step S1). Next, the diagnostic unit 12 of the diagnostic device 100 diagnoses an abnormality of the bearing using the acceleration judgment table 31, the speed judgment table 32, and the overall judgment tables 33, 33-1, and 33-2 based on the acquired acceleration data and speed data (step S2). Next, the display control unit 13 of the diagnostic device 100 displays the diagnosis result (step S3). The diagnosis result can include an acceleration diagnosis result obtained from the acceleration data and corresponding to the shaft diameter of the bearing, a speed diagnosis result obtained from the speed data and corresponding to the motor output of the motor that rotates the bearing, and an overall diagnosis result targeting the acceleration data and the speed data.

[0029] [summary] According to this embodiment, it is possible to diagnose abnormalities such as lack of oil or scratches in the rolling bearings from the acceleration data. Also, it is possible to diagnose abnormalities such as unbalance or misalignment of the bearings from the speed data. In this way, a lot of information can be obtained from the diagnosis results. Furthermore, with the recent spread of IoT (Internet of Things) devices, the number of targets for bearing abnormality diagnosis has expanded to a large number. In response to these circumstances, the present invention enables bearing abnormality diagnosis to be performed easily and over a wide area at an early stage, thereby improving the work efficiency of preventive equipment maintenance. In addition, the diagnostic results can be visualized, making it easy to identify abnormalities. In addition, by changing the weighting of the acceleration judgment and the weighting of the speed judgment in consideration of the installation environment and the number of years of installation, it is possible to quickly and reliably detect failures according to their cause without false alarms, which means that the accuracy of diagnosing bearing abnormalities can be improved.

[0030] [Variations] (a): In this embodiment, the overall diagnosis result is output using acceleration data and speed data indicating the vibration of the bearing. However, for example, the disturbance diagnosis result may also be output using displacement data indicating the vibration of the bearing. Specifically, for the bearing equipped in the target device, displacement data is acquired from at least one of the IoT sensor 1, the measuring device 2, and the tablet terminal 3. In addition, a three-dimensional judgment table using the acceleration data, the speed data, and the displacement data is prepared as the overall judgment table 33. Note that the overall judgment table using the acceleration data and the displacement data may be prepared, or the overall judgment table using the speed data and the displacement data may be prepared. (b): When the target device is inverter controlled (PWM (Pulse Width Modulation) method), the acceleration RMS may be strongly affected by inverter noise. Therefore, in this case, the diagnosing unit 12 may diagnose the bearing abnormality without using the acceleration judgment table 31. Specifically, it is preferable to output the overall diagnosis result by regarding the speed judgment table 32 as the overall judgment table 33. Note that when the target device is not inverter controlled (e.g., commercial operation) or is a PAM (Pulse Amplitude Modulation) method, it is preferable to apply the overall judgment of this embodiment. (c) In this embodiment, the tablet terminal 3 is taken as an example of an information terminal into which data related to the target device can be input. However, the information terminal may be, for example, a PC.

[0031] (d) It is also possible to realize a technology that appropriately combines the various technologies described in this embodiment. (e) The software described in this embodiment can be realized as hardware, and vice versa. (f) In addition, the hardware, software, flow charts, etc. may be modified as appropriate without departing from the spirit and scope of the present invention. [Explanation of symbols]

[0032] 100 Diagnostic Equipment 1 IoT Sensor 2 Measuring instrument 3. Tablet devices 11 Acquisition Department 12 Diagnostic Department 13 Display control section 21 Basic information DB 22 Measurement information DB 31 Acceleration Judgment Table 32 Speed ​​Judgment Table 33 Overall Judgment Table

Claims

1. an acquisition unit for acquiring acceleration data and velocity data indicative of vibration of the bearing; a diagnosis unit that diagnoses an abnormality in the bearing based on the acquired acceleration data and speed data.

2. 2. The diagnostic device according to claim 1, further comprising a display control unit that displays an acceleration diagnosis result obtained from the acceleration data and corresponding to a shaft diameter of the bearing, a speed diagnosis result obtained from the speed data and corresponding to a motor output of a motor that rotationally drives the bearing, and a comprehensive diagnosis result covering the acceleration data and the speed data.

3. 3. The diagnostic device according to claim 1, wherein the diagnosing unit diagnoses an abnormality in the bearing based on at least one of an installation environment of a device including the bearing and a number of years since the device was installed.

4. obtaining acceleration and velocity data indicative of vibrations of the bearing; and diagnosing an abnormality in the bearing based on the acquired acceleration data and velocity data.

Images